Triple
T1409353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bollywood cinema |
E31769
|
entity |
| Predicate | usesNarrativeStyle |
P26602
|
FINISHED |
| Object | interwoven songs and narrative |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: interwoven songs and narrative | Statement: [Bollywood cinema, usesNarrativeStyle, interwoven songs and narrative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNarrativeStyle Context triple: [Bollywood cinema, usesNarrativeStyle, interwoven songs and narrative]
-
A.
narrativeStyle
Indicates how a narrative is told, such as the point of view, tone, and structural approach used to present a story or account.
-
B.
hasNarrative
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
-
C.
narrativeType
Indicates the specific kind or category of narrative (e.g., genre, structural form, or storytelling mode) associated with an entity.
-
D.
containsNarrativeOf
Indicates that one entity includes or presents the story, account, or narrative content of another entity.
-
E.
narrativePassage
Indicates that a segment of text functions as a narrative passage, conveying events, actions, or storytelling rather than exposition, dialogue, or other discourse types.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3c10f44819085e1c4601423740d |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bf048b648190ab77d9b45cb4855f |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bf8158ac8190b8360ecccc2980bc |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:59 p.m.